xgboost/doc/index.md

XGBoost Documentation

This is document of xgboost library. XGBoost is short for eXtreme gradient boosting. This is a library that is designed, and optimized for boosted (tree) algorithms. The goal of this library is to push the extreme of the computation limits of machines to provide a scalable, portable and accurate for large scale tree boosting.

This document is hosted at http://xgboost.readthedocs.org/. You can also browse most of the documents in github directly.

User Guide

• Installation Guide
• Introduction to Boosted Trees
• Python Package Document
• R Package Document
• XGBoost.jl Julia Package
• Distributed Training
• Frequently Asked Questions
• External Memory Version
• Learning to use XGBoost by Example
• Parameters
• Text input format
• Notes on Parameter Tunning

Developer Guide

• Contributor Guide

Tutorials

Tutorials are self contained materials that teaches you how to achieve a complete data science task with xgboost, these are great resources to learn xgboost by real examples. If you think you have something that belongs to here, send a pull request.

• Binary classification using XGBoost Command Line (CLI)
  • This tutorial introduces the basic usage of CLI version of xgboost
• Introduction of XGBoost in Python (python)
  • This tutorial introduces the python package of xgboost
• Introduction to XGBoost in R (R package)
  • This is a general presentation about xgboost in R.
• Discover your data with XGBoost in R (R package)
  • This tutorial explaining feature analysis in xgboost.
• Understanding XGBoost Model on Otto Dataset (R package)
  • This tutorial teaches you how to use xgboost to compete kaggle otto challenge.

Resources

See awesome xgboost page for links to other resources.

Indices and tables

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`